Auto-framing based on user camera movement
Tomoya Sawada, Masahiro Toyoura, Xiaoyang Mao · 2017
We propose a novel approach to assisting users with searching the optimal composition of a photograph. In existing studies, the process of detecting the object in a given photo occurred via only image processing, however the result does not always include the object of user's interest. A major technique contribution of our approach is to exploit the user's motion to understand the user's subjective interest in a scene. User's subjective interest and objective structure information of the scene are combined to estimate the best composition based on aesthetic measures. We named this system Auto-Framing. The evaluation result shows that estimated optimal composition closes to the ground-truth. We will embed our technique in an actual camera to enable both automatic detection of compositions and real-time guidance functionality.